Overview

Dataset statistics

Number of variables16
Number of observations3652
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory456.6 KiB
Average record size in memory128.0 B

Variable types

DateTime1
TimeSeries15

Timeseries statistics

Number of series15
Time series length3652
Starting point0
Ending point3651
Period1
2024-05-16T03:59:33.979259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:34.459727image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Alerts

aportes_energia is highly overall correlated with gen_termica and 1 other fieldsHigh correlation
demanda is highly overall correlated with disp_dec_hidraulica and 4 other fieldsHigh correlation
disp_dec_hidraulica is highly overall correlated with demanda and 4 other fieldsHigh correlation
disp_dec_termica is highly overall correlated with demanda and 3 other fieldsHigh correlation
disponibilidad_declarada is highly overall correlated with demanda and 4 other fieldsHigh correlation
gen_hidraulica is highly overall correlated with demanda and 4 other fieldsHigh correlation
gen_termica is highly overall correlated with aportes_energia and 4 other fieldsHigh correlation
generacion is highly overall correlated with demanda and 4 other fieldsHigh correlation
precio_bolsa is highly overall correlated with gen_termica and 3 other fieldsHigh correlation
precio_oferta is highly overall correlated with gen_termica and 3 other fieldsHigh correlation
indice_ONI is highly overall correlated with precio_bolsa and 1 other fieldsHigh correlation
vertimientos is highly overall correlated with aportes_energia and 3 other fieldsHigh correlation
aportes_energia is non stationaryNon stationary
demanda is non stationaryNon stationary
disp_dec_hidraulica is non stationaryNon stationary
disp_dec_no_termica is non stationaryNon stationary
disp_dec_termica is non stationaryNon stationary
disponibilidad_declarada is non stationaryNon stationary
gen_hidraulica is non stationaryNon stationary
gen_no_termica is non stationaryNon stationary
gen_termica is non stationaryNon stationary
generacion is non stationaryNon stationary
precio_bolsa is non stationaryNon stationary
precio_oferta is non stationaryNon stationary
vol_util is non stationaryNon stationary
indice_ONI is non stationaryNon stationary
vertimientos is non stationaryNon stationary
aportes_energia is seasonalSeasonal
demanda is seasonalSeasonal
disp_dec_hidraulica is seasonalSeasonal
disp_dec_no_termica is seasonalSeasonal
disp_dec_termica is seasonalSeasonal
disponibilidad_declarada is seasonalSeasonal
gen_hidraulica is seasonalSeasonal
gen_no_termica is seasonalSeasonal
gen_termica is seasonalSeasonal
generacion is seasonalSeasonal
precio_bolsa is seasonalSeasonal
precio_oferta is seasonalSeasonal
vol_util is seasonalSeasonal
indice_ONI is seasonalSeasonal
vertimientos is seasonalSeasonal
fecha has unique valuesUnique
demanda has unique valuesUnique
gen_hidraulica has unique valuesUnique
gen_no_termica has unique valuesUnique
gen_termica has unique valuesUnique
generacion has unique valuesUnique
precio_bolsa has unique valuesUnique
indice_ONI has 121 (3.3%) zerosZeros
vertimientos has 1670 (45.7%) zerosZeros

Reproduction

Analysis started2024-05-16 03:58:15.446651
Analysis finished2024-05-16 03:59:33.732383
Duration1 minute and 18.29 seconds
Software versionydata-profiling vv4.6.0
Download configurationconfig.json

Variables

fecha
Date

UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
Minimum2010-01-01 00:00:00
Maximum2019-12-31 00:00:00
2024-05-16T03:59:34.982181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:35.261810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

aportes_energia
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct3651
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5554873 × 108
Minimum29032100
Maximum5.912453 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:35.539510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum29032100
5-th percentile58434865
Q11.019486 × 108
median1.438747 × 108
Q31.9203145 × 108
95-th percentile2.9503848 × 108
Maximum5.912453 × 108
Range5.622132 × 108
Interquartile range (IQR)90082850

Descriptive statistics

Standard deviation75143314
Coefficient of variation (CV)0.48308535
Kurtosis2.0388816
Mean1.5554873 × 108
Median Absolute Deviation (MAD)44154000
Skewness1.1393987
Sum5.6806397 × 1011
Variance5.6465176 × 1015
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value3.095400219 × 10-7
2024-05-16T03:59:35.819650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:36.619153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:36.813806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
67561900 2
 
0.1%
45616100 1
 
< 0.1%
118214500 1
 
< 0.1%
153039000 1
 
< 0.1%
201372100 1
 
< 0.1%
165531300 1
 
< 0.1%
117343900 1
 
< 0.1%
190736600 1
 
< 0.1%
129762900 1
 
< 0.1%
299613500 1
 
< 0.1%
Other values (3641) 3641
99.7%
ValueCountFrequency (%)
29032100 1
< 0.1%
30175300 1
< 0.1%
31084900 1
< 0.1%
31612700 1
< 0.1%
31863500 1
< 0.1%
32256000 1
< 0.1%
32331600 1
< 0.1%
32688100 1
< 0.1%
34106500 1
< 0.1%
34225400 1
< 0.1%
ValueCountFrequency (%)
591245300 1
< 0.1%
538753100 1
< 0.1%
517632300 1
< 0.1%
513359500 1
< 0.1%
501525500 1
< 0.1%
493823300 1
< 0.1%
479942900 1
< 0.1%
476524100 1
< 0.1%
466501400 1
< 0.1%
464266000 1
< 0.1%
2024-05-16T03:59:36.146685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

demanda
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.734175 × 108
Minimum1.1336158 × 108
Maximum2.1377837 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:37.108174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.1336158 × 108
5-th percentile1.4206551 × 108
Q11.6116639 × 108
median1.749549 × 108
Q31.8661133 × 108
95-th percentile1.9929525 × 108
Maximum2.1377837 × 108
Range1.0041679 × 108
Interquartile range (IQR)25444937

Descriptive statistics

Standard deviation17194643
Coefficient of variation (CV)0.099151714
Kurtosis-0.32831051
Mean1.734175 × 108
Median Absolute Deviation (MAD)12763205
Skewness-0.33427522
Sum6.3332072 × 1011
Variance2.9565574 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.07816467668
2024-05-16T03:59:37.400891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:38.173873image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:38.373044image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
113361581.1 1
 
< 0.1%
192439811.6 1
 
< 0.1%
192158157.8 1
 
< 0.1%
184706893.7 1
 
< 0.1%
176515164.9 1
 
< 0.1%
159273857 1
 
< 0.1%
187831120 1
 
< 0.1%
188168921.3 1
 
< 0.1%
185787276.4 1
 
< 0.1%
182397651.4 1
 
< 0.1%
Other values (3642) 3642
99.7%
ValueCountFrequency (%)
113361581.1 1
< 0.1%
116040630.8 1
< 0.1%
118210996.3 1
< 0.1%
119802775.3 1
< 0.1%
120631870 1
< 0.1%
120802656.8 1
< 0.1%
121145172.8 1
< 0.1%
123249822.9 1
< 0.1%
123639155.1 1
< 0.1%
124105908.8 1
< 0.1%
ValueCountFrequency (%)
213778370.7 1
< 0.1%
212846328.8 1
< 0.1%
212673471.5 1
< 0.1%
211439363.3 1
< 0.1%
211396980.8 1
< 0.1%
211342050.9 1
< 0.1%
211168017 1
< 0.1%
210941393.7 1
< 0.1%
210658179.4 1
< 0.1%
210589769.8 1
< 0.1%
2024-05-16T03:59:37.707448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

disp_dec_hidraulica
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct3551
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0542766 × 108
Minimum1.3278788 × 108
Maximum2.4922814 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:38.658712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.3278788 × 108
5-th percentile1.75352 × 108
Q11.904658 × 108
median2.028157 × 108
Q32.225033 × 108
95-th percentile2.397299 × 108
Maximum2.4922814 × 108
Range1.1644026 × 108
Interquartile range (IQR)32037500

Descriptive statistics

Standard deviation20612319
Coefficient of variation (CV)0.10033858
Kurtosis-0.57585254
Mean2.0542766 × 108
Median Absolute Deviation (MAD)15294115
Skewness0.034527429
Sum7.5022182 × 1011
Variance4.2486769 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.03329192644
2024-05-16T03:59:38.963586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:40.291949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:40.610523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
185760000 4
 
0.1%
212832000 4
 
0.1%
181428000 3
 
0.1%
206112000 3
 
0.1%
192120000 3
 
0.1%
196200000 3
 
0.1%
187424000 3
 
0.1%
200688000 3
 
0.1%
202704000 3
 
0.1%
187872000 3
 
0.1%
Other values (3541) 3620
99.1%
ValueCountFrequency (%)
132787880 1
< 0.1%
133655080 1
< 0.1%
134811400 1
< 0.1%
138681920 1
< 0.1%
140516520 1
< 0.1%
142620920 1
< 0.1%
143771320 1
< 0.1%
145537920 1
< 0.1%
148465260 1
< 0.1%
148993000 1
< 0.1%
ValueCountFrequency (%)
249228140 1
< 0.1%
248312420 1
< 0.1%
248128050 1
< 0.1%
248110290 1
< 0.1%
247891920 1
< 0.1%
247796800 1
< 0.1%
247418940 1
< 0.1%
247403540 1
< 0.1%
247324660 1
< 0.1%
247102140 1
< 0.1%
2024-05-16T03:59:39.563366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

disp_dec_no_termica
Numeric time series

NON STATIONARY  SEASONAL 

Distinct1564
Distinct (%)42.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9023437.5
Minimum0
Maximum14592000
Zeros6
Zeros (%)0.2%
Memory size28.7 KiB
2024-05-16T03:59:41.116759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7429000
Q17536000
median8053080
Q310671380
95-th percentile12140000
Maximum14592000
Range14592000
Interquartile range (IQR)3135380

Descriptive statistics

Standard deviation2226650.7
Coefficient of variation (CV)0.24676302
Kurtosis1.4884492
Mean9023437.5
Median Absolute Deviation (MAD)565080
Skewness-0.19404593
Sum3.2953594 × 1010
Variance4.9579733 × 1012
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.0001461977619
2024-05-16T03:59:41.666764image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:43.079637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:43.437767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
7536000 767
21.0%
7488000 229
 
6.3%
8053080 160
 
4.4%
7933080 152
 
4.2%
7981080 91
 
2.5%
7693080 90
 
2.5%
7848000 79
 
2.2%
7671000 63
 
1.7%
10536000 59
 
1.6%
14470000 45
 
1.2%
Other values (1554) 1917
52.5%
ValueCountFrequency (%)
0 6
0.2%
1067680 1
 
< 0.1%
1074680 2
 
0.1%
1089390 1
 
< 0.1%
1090840 1
 
< 0.1%
1102400 5
0.1%
1282400 1
 
< 0.1%
1329390 1
 
< 0.1%
1342400 1
 
< 0.1%
1344400 1
 
< 0.1%
ValueCountFrequency (%)
14592000 26
0.7%
14544000 6
 
0.2%
14518000 2
 
0.1%
14510000 2
 
0.1%
14470000 45
1.2%
14442000 1
 
< 0.1%
14433000 3
 
0.1%
14370000 2
 
0.1%
14350000 6
 
0.2%
14064000 1
 
< 0.1%
2024-05-16T03:59:42.262177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

disp_dec_termica
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct3227
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85910686
Minimum52649000
Maximum1.1202165 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:43.982686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum52649000
5-th percentile66360000
Q178273000
median86920500
Q393471182
95-th percentile1.0216845 × 108
Maximum1.1202165 × 108
Range59372650
Interquartile range (IQR)15198182

Descriptive statistics

Standard deviation10929794
Coefficient of variation (CV)0.12722275
Kurtosis-0.27889797
Mean85910686
Median Absolute Deviation (MAD)7675010
Skewness-0.27867764
Sum3.1374583 × 1011
Variance1.194604 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.03732081229
2024-05-16T03:59:44.559852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:46.008888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:46.389601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
69312000 11
 
0.3%
73296000 10
 
0.3%
77817000 7
 
0.2%
82176000 7
 
0.2%
83520000 7
 
0.2%
76536000 7
 
0.2%
78600000 7
 
0.2%
78336000 6
 
0.2%
78168000 6
 
0.2%
78183000 6
 
0.2%
Other values (3217) 3578
98.0%
ValueCountFrequency (%)
52649000 1
< 0.1%
52810000 1
< 0.1%
53513000 1
< 0.1%
54468000 1
< 0.1%
55003000 1
< 0.1%
55083000 1
< 0.1%
55244000 1
< 0.1%
55622000 1
< 0.1%
56098000 2
0.1%
56290000 1
< 0.1%
ValueCountFrequency (%)
112021650 1
< 0.1%
111876050 1
< 0.1%
111618660 1
< 0.1%
111151450 1
< 0.1%
111006110 1
< 0.1%
110918150 1
< 0.1%
110909050 1
< 0.1%
110750450 1
< 0.1%
110724890 1
< 0.1%
110699220 1
< 0.1%
2024-05-16T03:59:45.191176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

disponibilidad_declarada
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct3628
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0036178 × 108
Minimum2.2001616 × 108
Maximum3.6733167 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:46.894886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2.2001616 × 108
5-th percentile2.5730255 × 108
Q12.78451 × 108
median2.9540862 × 108
Q33.2603974 × 108
95-th percentile3.4805998 × 108
Maximum3.6733167 × 108
Range1.4731551 × 108
Interquartile range (IQR)47588738

Descriptive statistics

Standard deviation29022363
Coefficient of variation (CV)0.096624684
Kurtosis-0.90112952
Mean3.0036178 × 108
Median Absolute Deviation (MAD)22993470
Skewness0.10559714
Sum1.0969212 × 1012
Variance8.4229754 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.1152008331
2024-05-16T03:59:47.414630image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:48.749833image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:48.950657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
278933000 2
 
0.1%
292008000 2
 
0.1%
272997000 2
 
0.1%
267092000 2
 
0.1%
260745000 2
 
0.1%
289104000 2
 
0.1%
295709000 2
 
0.1%
298395880 2
 
0.1%
295102000 2
 
0.1%
272594000 2
 
0.1%
Other values (3618) 3632
99.5%
ValueCountFrequency (%)
220016160 1
< 0.1%
223823480 1
< 0.1%
224735960 1
< 0.1%
227289000 1
< 0.1%
227745000 1
< 0.1%
228499400 1
< 0.1%
230948000 1
< 0.1%
231465000 1
< 0.1%
232243000 1
< 0.1%
233287000 1
< 0.1%
ValueCountFrequency (%)
367331670 1
< 0.1%
364309890 1
< 0.1%
364308230 1
< 0.1%
364030650 1
< 0.1%
363693490 1
< 0.1%
363499940 1
< 0.1%
362918250 1
< 0.1%
361233230 1
< 0.1%
361124170 1
< 0.1%
360790130 1
< 0.1%
2024-05-16T03:59:48.052212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

gen_hidraulica
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3246306 × 108
Minimum35796805
Maximum1.8059647 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:49.229966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum35796805
5-th percentile90646009
Q11.1917195 × 108
median1.3390377 × 108
Q31.4635024 × 108
95-th percentile1.691969 × 108
Maximum1.8059647 × 108
Range1.4479967 × 108
Interquartile range (IQR)27178287

Descriptive statistics

Standard deviation23052628
Coefficient of variation (CV)0.17403061
Kurtosis0.43847524
Mean1.3246306 × 108
Median Absolute Deviation (MAD)13636408
Skewness-0.48686348
Sum4.837551 × 1011
Variance5.3142364 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.002611728426
2024-05-16T03:59:49.523957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:50.333404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:50.539766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
35796804.67 1
 
< 0.1%
149834312 1
 
< 0.1%
139567755.2 1
 
< 0.1%
132570640.4 1
 
< 0.1%
136120299.4 1
 
< 0.1%
105327209.9 1
 
< 0.1%
142248835.2 1
 
< 0.1%
154131032.7 1
 
< 0.1%
147544869.8 1
 
< 0.1%
145098341.1 1
 
< 0.1%
Other values (3642) 3642
99.7%
ValueCountFrequency (%)
35796804.67 1
< 0.1%
42578875.2 1
< 0.1%
45571402.58 1
< 0.1%
46595646.99 1
< 0.1%
52101331.16 1
< 0.1%
52285897.36 1
< 0.1%
52938290.06 1
< 0.1%
54014433.37 1
< 0.1%
54051541.1 1
< 0.1%
55397788.91 1
< 0.1%
ValueCountFrequency (%)
180596472.3 1
< 0.1%
179075334.7 1
< 0.1%
178835869.4 1
< 0.1%
178746599.3 1
< 0.1%
178701632.5 1
< 0.1%
178474626.4 1
< 0.1%
178356701.6 1
< 0.1%
178094405 1
< 0.1%
177978044.1 1
< 0.1%
177837965.9 1
< 0.1%
2024-05-16T03:59:49.866555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

gen_no_termica
Numeric time series

NON STATIONARY  SEASONAL  UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3959264.2
Minimum1328458.1
Maximum17256610
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:50.851217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1328458.1
5-th percentile2294925.1
Q12960760
median3451657.2
Q34091159.6
95-th percentile7215818.7
Maximum17256610
Range15928152
Interquartile range (IQR)1130399.6

Descriptive statistics

Standard deviation2160212.1
Coefficient of variation (CV)0.54560948
Kurtosis13.918325
Mean3959264.2
Median Absolute Deviation (MAD)554831.37
Skewness3.54014
Sum1.4459233 × 1010
Variance4.6665163 × 1012
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value4.336782316 × 10-8
2024-05-16T03:59:51.156776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:51.986043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:52.192544image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
13362226.83 1
 
< 0.1%
3605055.72 1
 
< 0.1%
3348015.54 1
 
< 0.1%
3322341.83 1
 
< 0.1%
3451950.68 1
 
< 0.1%
3593076.98 1
 
< 0.1%
3413603.87 1
 
< 0.1%
3697489.86 1
 
< 0.1%
3553393.07 1
 
< 0.1%
3016142.93 1
 
< 0.1%
Other values (3642) 3642
99.7%
ValueCountFrequency (%)
1328458.12 1
< 0.1%
1572660.58 1
< 0.1%
1583225 1
< 0.1%
1594286.65 1
< 0.1%
1596804.15 1
< 0.1%
1602387.29 1
< 0.1%
1681894.84 1
< 0.1%
1688472.89 1
< 0.1%
1695659.74 1
< 0.1%
1699593.21 1
< 0.1%
ValueCountFrequency (%)
17256610.16 1
< 0.1%
17137258.82 1
< 0.1%
16934994.81 1
< 0.1%
16637618.9 1
< 0.1%
16628638.54 1
< 0.1%
16599627.14 1
< 0.1%
16130689.7 1
< 0.1%
16122898.21 1
< 0.1%
15972151.07 1
< 0.1%
15870248.17 1
< 0.1%
2024-05-16T03:59:51.487899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

gen_termica
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38890353
Minimum11977677
Maximum93572611
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:52.491654image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum11977677
5-th percentile17611226
Q124764742
median35646471
Q349940928
95-th percentile74003913
Maximum93572611
Range81594934
Interquartile range (IQR)25176186

Descriptive statistics

Standard deviation17166546
Coefficient of variation (CV)0.44140884
Kurtosis0.25396811
Mean38890353
Median Absolute Deviation (MAD)12319743
Skewness0.82556806
Sum1.4202757 × 1011
Variance2.9469029 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.01116122188
2024-05-16T03:59:52.788545image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:54.231908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:54.433464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
66260052.96 1
 
< 0.1%
41222742.92 1
 
< 0.1%
51228034.66 1
 
< 0.1%
51046565.94 1
 
< 0.1%
38973414.5 1
 
< 0.1%
44140706.39 1
 
< 0.1%
41815380.6 1
 
< 0.1%
33390586.67 1
 
< 0.1%
37165106.87 1
 
< 0.1%
36447528.31 1
 
< 0.1%
Other values (3642) 3642
99.7%
ValueCountFrequency (%)
11977677.16 1
< 0.1%
12157256.13 1
< 0.1%
12173643.1 1
< 0.1%
12540482.94 1
< 0.1%
12544763.64 1
< 0.1%
12552780.2 1
< 0.1%
12560038.92 1
< 0.1%
12607316.04 1
< 0.1%
12976561.95 1
< 0.1%
13239947.29 1
< 0.1%
ValueCountFrequency (%)
93572611.08 1
< 0.1%
92644930.41 1
< 0.1%
92379950.75 1
< 0.1%
91577369.54 1
< 0.1%
91426756.91 1
< 0.1%
91410918.59 1
< 0.1%
91302039.74 1
< 0.1%
91138574.85 1
< 0.1%
91137928.91 1
< 0.1%
90974323.92 1
< 0.1%
2024-05-16T03:59:53.740855image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

generacion
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7531268 × 108
Minimum1.1541908 × 108
Maximum2.1515442 × 108
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:54.709821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1.1541908 × 108
5-th percentile1.4453824 × 108
Q11.6362338 × 108
median1.7712357 × 108
Q31.8861736 × 108
95-th percentile1.9965355 × 108
Maximum2.1515442 × 108
Range99735335
Interquartile range (IQR)24993980

Descriptive statistics

Standard deviation16700754
Coefficient of variation (CV)0.095262672
Kurtosis-0.29836689
Mean1.7531268 × 108
Median Absolute Deviation (MAD)12378205
Skewness-0.42108878
Sum6.4024191 × 1011
Variance2.789152 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.03308116094
2024-05-16T03:59:55.010758image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:55.797282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:56.011091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
115419084.5 1
 
< 0.1%
194662110.7 1
 
< 0.1%
194143805.4 1
 
< 0.1%
186939548.2 1
 
< 0.1%
178545664.6 1
 
< 0.1%
153060993.3 1
 
< 0.1%
187477819.7 1
 
< 0.1%
191219109.3 1
 
< 0.1%
188263369.7 1
 
< 0.1%
184562012.4 1
 
< 0.1%
Other values (3642) 3642
99.7%
ValueCountFrequency (%)
115419084.5 1
< 0.1%
118404551.6 1
< 0.1%
120675610.7 1
< 0.1%
121906176.6 1
< 0.1%
122492686.7 1
< 0.1%
123002371.3 1
< 0.1%
123637778.4 1
< 0.1%
125706564.9 1
< 0.1%
125904027.6 1
< 0.1%
126583191.1 1
< 0.1%
ValueCountFrequency (%)
215154419.4 1
< 0.1%
213384747 1
< 0.1%
212131752.4 1
< 0.1%
211978742 1
< 0.1%
210704542.9 1
< 0.1%
210274858.8 1
< 0.1%
209384685.1 1
< 0.1%
209375576.7 1
< 0.1%
209247962.7 1
< 0.1%
208977573.5 1
< 0.1%
2024-05-16T03:59:55.317426image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

precio_bolsa
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  UNIQUE 

Distinct3652
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean185.08419
Minimum35.356673
Maximum1942.6928
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:56.298802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum35.356673
5-th percentile58.157671
Q195.595586
median146.23322
Q3194.49072
95-th percentile470.13159
Maximum1942.6928
Range1907.3361
Interquartile range (IQR)98.895135

Descriptive statistics

Standard deviation170.13092
Coefficient of variation (CV)0.91920823
Kurtosis24.149947
Mean185.08419
Median Absolute Deviation (MAD)49.582455
Skewness4.0062353
Sum675927.48
Variance28944.528
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.0002560506497
2024-05-16T03:59:56.669100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T03:59:57.960601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T03:59:58.210139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
120.5012283 1
 
< 0.1%
275.7879567 1
 
< 0.1%
309.74885 1
 
< 0.1%
294.981625 1
 
< 0.1%
240.2986783 1
 
< 0.1%
272.82091 1
 
< 0.1%
222.6077333 1
 
< 0.1%
172.1206967 1
 
< 0.1%
209.669325 1
 
< 0.1%
172.6748433 1
 
< 0.1%
Other values (3642) 3642
99.7%
ValueCountFrequency (%)
35.35667333 1
< 0.1%
36.11690333 1
< 0.1%
37.493925 1
< 0.1%
37.75055 1
< 0.1%
38.23312333 1
< 0.1%
38.397985 1
< 0.1%
38.56781 1
< 0.1%
38.585665 1
< 0.1%
38.59078333 1
< 0.1%
38.6379 1
< 0.1%
ValueCountFrequency (%)
1942.692797 1
< 0.1%
1892.82874 1
< 0.1%
1866.382907 1
< 0.1%
1847.67874 1
< 0.1%
1846.63167 1
< 0.1%
1803.7993 1
< 0.1%
1705.072668 1
< 0.1%
1631.773657 1
< 0.1%
1233.933323 1
< 0.1%
1223.75822 1
< 0.1%
2024-05-16T03:59:57.223680image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

precio_oferta
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL 

Distinct3649
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean301.26058
Minimum188.07752
Maximum736.06255
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T03:59:58.621971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum188.07752
5-th percentile207.74505
Q1245.61217
median290.59795
Q3336.84995
95-th percentile439.98711
Maximum736.06255
Range547.98503
Interquartile range (IQR)91.237778

Descriptive statistics

Standard deviation72.950289
Coefficient of variation (CV)0.24215013
Kurtosis3.1171965
Mean301.26058
Median Absolute Deviation (MAD)45.489681
Skewness1.3805822
Sum1100203.6
Variance5321.7447
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.01003061117
2024-05-16T03:59:59.102578image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T04:00:00.492754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T04:00:00.821958image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
425.4984717 2
 
0.1%
236.8788958 2
 
0.1%
266.5086667 2
 
0.1%
284.3154717 1
 
< 0.1%
285.9689245 1
 
< 0.1%
280.6370189 1
 
< 0.1%
311.875 1
 
< 0.1%
303.2716604 1
 
< 0.1%
292.0420189 1
 
< 0.1%
277.319717 1
 
< 0.1%
Other values (3639) 3639
99.6%
ValueCountFrequency (%)
188.0775208 1
< 0.1%
189.257125 1
< 0.1%
189.9019787 1
< 0.1%
190.1385 1
< 0.1%
190.5878333 1
< 0.1%
192.1800208 1
< 0.1%
192.3106042 1
< 0.1%
194.826234 1
< 0.1%
195.5067292 1
< 0.1%
195.8980638 1
< 0.1%
ValueCountFrequency (%)
736.062549 1
< 0.1%
718.3006 1
< 0.1%
679.3509 1
< 0.1%
656.9518039 1
< 0.1%
652.9239412 1
< 0.1%
643.3446863 1
< 0.1%
640.0135686 1
< 0.1%
637.0736471 1
< 0.1%
636.6128235 1
< 0.1%
634.395 1
< 0.1%
2024-05-16T03:59:59.688485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

vol_util
Numeric time series

NON STATIONARY  SEASONAL 

Distinct3651
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0525712 × 1010
Minimum5.7766728 × 109
Maximum1.4501579 × 1010
Zeros0
Zeros (%)0.0%
Memory size28.7 KiB
2024-05-16T04:00:01.254712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum5.7766728 × 109
5-th percentile6.8642649 × 109
Q18.8618089 × 109
median1.0745912 × 1010
Q31.2364036 × 1010
95-th percentile1.3637343 × 1010
Maximum1.4501579 × 1010
Range8.7249064 × 109
Interquartile range (IQR)3.5022272 × 109

Descriptive statistics

Standard deviation2.1656216 × 109
Coefficient of variation (CV)0.20574585
Kurtosis-1.0144577
Mean1.0525712 × 1010
Median Absolute Deviation (MAD)1.7089679 × 109
Skewness-0.27849214
Sum3.8439901 × 1013
Variance4.6899169 × 1018
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value5.88883751 × 10-6
2024-05-16T04:00:01.647194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T04:00:02.432222image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T04:00:02.626188image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
1.37165262 × 10102
 
0.1%
1.000661478 × 10101
 
< 0.1%
9877672100 1
 
< 0.1%
9669706500 1
 
< 0.1%
9674270400 1
 
< 0.1%
9729730800 1
 
< 0.1%
9786008700 1
 
< 0.1%
9748662700 1
 
< 0.1%
9763371300 1
 
< 0.1%
9733165600 1
 
< 0.1%
Other values (3641) 3641
99.7%
ValueCountFrequency (%)
5776672751 1
< 0.1%
5791685510 1
< 0.1%
5813829408 1
< 0.1%
5815967862 1
< 0.1%
5817398807 1
< 0.1%
5821011642 1
< 0.1%
5828231740 1
< 0.1%
5841081792 1
< 0.1%
5841547854 1
< 0.1%
5843125127 1
< 0.1%
ValueCountFrequency (%)
1.450157914 × 10101
< 0.1%
1.449806977 × 10101
< 0.1%
1.449207431 × 10101
< 0.1%
1.44822665 × 10101
< 0.1%
1.447542961 × 10101
< 0.1%
1.447225119 × 10101
< 0.1%
1.446984447 × 10101
< 0.1%
1.446956342 × 10101
< 0.1%
1.446097317 × 10101
< 0.1%
1.445400255 × 10101
< 0.1%
2024-05-16T04:00:01.961074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

indice_ONI
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  ZEROS 

Distinct34
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.036801752
Minimum-1.6
Maximum2.6
Zeros121
Zeros (%)3.3%
Memory size28.7 KiB
2024-05-16T04:00:02.893217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-1.6
5-th percentile-1.3
Q1-0.525
median0
Q30.5
95-th percentile1.9
Maximum2.6
Range4.2
Interquartile range (IQR)1.025

Descriptive statistics

Standard deviation0.88272223
Coefficient of variation (CV)23.985875
Kurtosis0.88829618
Mean0.036801752
Median Absolute Deviation (MAD)0.5
Skewness0.79841136
Sum134.4
Variance0.77919853
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.1719389236
2024-05-16T04:00:03.137245image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
2024-05-16T04:00:03.906094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T04:00:04.082145image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
0.5 273
 
7.5%
-0.4 273
 
7.5%
-0.3 246
 
6.7%
0.2 213
 
5.8%
-0.7 212
 
5.8%
0.1 185
 
5.1%
-0.2 182
 
5.0%
0.7 181
 
5.0%
-0.6 154
 
4.2%
0.3 154
 
4.2%
Other values (24) 1579
43.2%
ValueCountFrequency (%)
-1.6 122
3.3%
-1.4 31
 
0.8%
-1.3 31
 
0.8%
-1.2 28
 
0.8%
-1.1 30
 
0.8%
-1 124
3.4%
-0.9 121
3.3%
-0.8 60
 
1.6%
-0.7 212
5.8%
-0.6 154
4.2%
ValueCountFrequency (%)
2.6 61
1.7%
2.5 31
 
0.8%
2.4 31
 
0.8%
2.2 30
 
0.8%
2.1 29
 
0.8%
1.9 31
 
0.8%
1.6 31
 
0.8%
1.5 62
1.7%
1.2 58
1.6%
0.9 91
2.5%
2024-05-16T04:00:03.434506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

vertimientos
Numeric time series

HIGH CORRELATION  NON STATIONARY  SEASONAL  ZEROS 

Distinct1979
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6523732.3
Minimum0
Maximum1.3671901 × 108
Zeros1670
Zeros (%)45.7%
Memory size28.7 KiB
2024-05-16T04:00:04.332913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median205744.42
Q35390189
95-th percentile36600362
Maximum1.3671901 × 108
Range1.3671901 × 108
Interquartile range (IQR)5390189

Descriptive statistics

Standard deviation14084754
Coefficient of variation (CV)2.1590025
Kurtosis14.246638
Mean6523732.3
Median Absolute Deviation (MAD)205744.42
Skewness3.3952147
Sum2.382467 × 1010
Variance1.983803 × 1014
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value3.689472064 × 10-8
2024-05-16T04:00:04.652011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2024-05-16T04:00:05.470139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Gap statistics

number of gaps0
minnan
maxnan
meannan
std0
2024-05-16T04:00:05.670899image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
0 1670
45.7%
209120.6322 2
 
0.1%
5373.61555 2
 
0.1%
868847.424 2
 
0.1%
59869 2
 
0.1%
27329833.92 1
 
< 0.1%
20116846.8 1
 
< 0.1%
26523604.38 1
 
< 0.1%
12903083.1 1
 
< 0.1%
316313.2608 1
 
< 0.1%
Other values (1969) 1969
53.9%
ValueCountFrequency (%)
0 1670
45.7%
43.87172 1
 
< 0.1%
159.168 1
 
< 0.1%
477.504 1
 
< 0.1%
585.408 1
 
< 0.1%
746.064 1
 
< 0.1%
822.71055 1
 
< 0.1%
825.264 1
 
< 0.1%
1143.36 1
 
< 0.1%
1273.54138 1
 
< 0.1%
ValueCountFrequency (%)
136719010 1
< 0.1%
120631598.4 1
< 0.1%
118182589.4 1
< 0.1%
108778609.9 1
< 0.1%
108242130.5 1
< 0.1%
107989794.3 1
< 0.1%
99757261.82 1
< 0.1%
92878770.84 1
< 0.1%
92545135.39 1
< 0.1%
90042400.22 1
< 0.1%
2024-05-16T04:00:04.982387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ACF and PACF

Interactions

2024-05-16T03:59:27.716766image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:23.963102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:29.382040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:33.162127image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:38.069848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:43.639586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:47.767565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:51.679070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:56.611735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:01.397199image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:05.351474image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:09.459910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:15.083973image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:18.931148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:22.741376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:28.078661image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:24.684024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:29.630559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:33.421865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:38.407146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:43.907648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:48.020893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:51.924107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:56.947854image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:01.671303image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:05.603166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:09.853564image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:15.328594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:19.175749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:22.975620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:28.483904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:25.037401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:29.904702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:34.743152image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:38.752957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:44.162359image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:48.264786image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:52.189471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:57.248055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:01.925308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:05.847478image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:10.212049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:15.575257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:19.418280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:23.209727image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:28.886308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:25.401491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:30.176718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:34.978076image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:39.087835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:44.409825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:48.524009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:52.449507image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:57.654508image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:02.184105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:06.088594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:10.593716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:15.823888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:19.669521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:23.457860image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:29.166639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:25.800747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:30.439637image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:35.231672image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:39.505670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:44.675907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:48.784957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:52.718464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:58.503686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:02.445942image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:06.345966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:11.008267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:16.087099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:19.936032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:23.794106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:29.432120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:26.182970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:30.685551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:35.499035image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:39.922629image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:44.950157image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:49.057062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:52.980438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:58.768949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:02.728180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:06.598432image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:11.426669image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:16.353139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:20.194971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:24.146008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:29.715035image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:26.576642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:30.948496image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:35.753189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:40.292600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:45.213557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:49.317052image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:53.263572image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:59.042814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:02.996315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:06.866338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:11.841579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:16.618055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:20.466045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:24.535761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:29.983717image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:26.999689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:31.205473image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:36.014769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:40.688250image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:45.479531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:49.586389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:53.689207image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:59.301479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:03.265016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:07.122949image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:12.731511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:16.883501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:20.722342image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:24.914835image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:30.252536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:27.400548image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:31.469088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:36.279480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:41.073864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:45.747718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:49.863917image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:54.040090image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:59.594407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:03.561280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:07.395016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:13.141244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:17.168334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:20.979813image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:25.267613image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:31.026121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:27.761543image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:31.725864image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:36.553442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:41.490546image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:46.031005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:50.142038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:54.402609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:59.866263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:03.829058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:07.660255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:13.532368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:17.435960image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:21.236111image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:25.655429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:31.282166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:28.113203image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:31.960102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:36.810032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:41.915943image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:46.281312image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:50.395418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:54.797910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:00.118194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:04.084104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:07.916763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:13.788948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:17.699678image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:21.489933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:25.910567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:31.546945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:28.381098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:32.214407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:37.079408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:42.310638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:46.813096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:50.664807image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:55.138558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:00.393010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:04.355453image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:08.179750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:14.085689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:17.955494image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:21.768692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:26.278918image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:31.816598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:28.629295image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:32.471900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:37.323304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:42.676957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:47.054456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:50.920656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:55.524224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:00.655105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:04.617285image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:08.420594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:14.332294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:18.202128image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:22.006659image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:26.658375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:32.062747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:28.886406image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:32.698648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:37.580284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:43.064914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:47.287837image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:51.173428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:55.907744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:00.893789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:04.856151image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:08.712718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:14.577320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:18.439750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:22.243649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:27.024160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:32.300232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:29.113378image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:32.908474image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:37.797966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:43.369956image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:47.518135image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:51.415701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:58:56.203246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:01.132579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:05.088103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:09.068665image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:14.813798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:18.678961image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:22.480895image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-05-16T03:59:27.332218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-05-16T04:00:05.936621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
aportes_energiademandadisp_dec_hidraulicadisp_dec_no_termicadisp_dec_termicadisponibilidad_declaradagen_hidraulicagen_no_termicagen_termicageneracionprecio_bolsaprecio_ofertavol_utilindice_ONIvertimientos
aportes_energia1.000-0.0300.1990.017-0.1550.0730.372-0.053-0.524-0.023-0.488-0.3380.285-0.2300.553
demanda-0.0301.0000.5350.3080.5920.6130.6180.2300.1290.9950.3070.2790.0570.377-0.110
disp_dec_hidraulica0.1990.5351.0000.3850.5930.9420.6240.209-0.3210.519-0.1060.0410.3360.1540.140
disp_dec_no_termica0.0170.3080.3851.0000.3100.4450.2980.435-0.1100.2860.022-0.167-0.1320.1810.060
disp_dec_termica-0.1550.5920.5930.3101.0000.8100.3010.1320.1310.5640.2800.354-0.1020.337-0.200
disponibilidad_declarada0.0730.6130.9420.4450.8101.0000.5630.206-0.1730.5890.0420.1650.1620.2450.006
gen_hidraulica0.3720.6180.6240.2980.3010.5631.0000.110-0.6330.628-0.410-0.3120.388-0.1230.352
gen_no_termica-0.0530.2300.2090.4350.1320.2060.1101.0000.0210.2080.057-0.0340.0800.2580.073
gen_termica-0.5240.129-0.321-0.1100.131-0.173-0.6330.0211.0000.1210.8480.645-0.4800.483-0.593
generacion-0.0230.9950.5190.2860.5640.5890.6280.2080.1211.0000.2850.2600.0800.358-0.093
precio_bolsa-0.4880.307-0.1060.0220.2800.042-0.4100.0570.8480.2851.0000.714-0.4770.562-0.629
precio_oferta-0.3380.2790.041-0.1670.3540.165-0.312-0.0340.6450.2600.7141.000-0.2510.574-0.501
vol_util0.2850.0570.336-0.132-0.1020.1620.3880.080-0.4800.080-0.477-0.2511.000-0.1230.495
indice_ONI-0.2300.3770.1540.1810.3370.245-0.1230.2580.4830.3580.5620.574-0.1231.000-0.364
vertimientos0.553-0.1100.1400.060-0.2000.0060.3520.073-0.593-0.093-0.629-0.5010.495-0.3641.000

Missing values

2024-05-16T03:59:32.698136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-16T03:59:33.459702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

fechaaportes_energiademandadisp_dec_hidraulicadisp_dec_no_termicadisp_dec_termicadisponibilidad_declaradagen_hidraulicagen_no_termicagen_termicageneracionprecio_bolsaprecio_ofertavol_utilindice_ONIvertimientos
02010-01-0145616100.01.133616e+08188034000.012314000.081723000.0282071000.035796804.6713362226.8366260052.961.154191e+08120.501228267.4376331.000661e+101.50.0
12010-01-0243097100.01.254718e+08186794000.012314000.081738000.0280846000.046595646.9913393741.6367691806.161.276812e+08118.495340277.1535929.995147e+091.50.0
22010-01-0343400400.01.211452e+08188274000.012314000.080274000.0280862000.042578875.2013046074.8368012828.411.236378e+08121.160145313.5527559.992677e+091.50.0
32010-01-0440410400.01.439317e+08180374000.012314000.078363000.0271051000.062242326.7913160643.9570554488.251.459575e+08123.962937303.5198789.965341e+091.50.0
42010-01-0541190600.01.498691e+08182754000.012314000.078364000.0273432000.069173462.6514514419.1568460147.291.521480e+08120.666437339.6004499.926760e+091.50.0
52010-01-0641733100.01.503796e+08178938000.012554000.075003000.0266495000.069723841.6314751943.8868450441.251.529262e+08125.920603331.6717969.886867e+091.50.0
62010-01-0739732000.01.497299e+08177087000.012554000.073318000.0262959000.072673134.5915217924.6964157331.381.520484e+08130.821518363.0252249.845174e+091.50.0
72010-01-0837078100.01.510875e+08181582000.012695000.075109000.0269386000.073179007.5713739421.3766883989.621.538024e+08153.068853363.8441849.805162e+091.50.0
82010-01-0946893900.01.438687e+08179058000.014064000.073642000.0266764000.067593662.0915079280.0663824175.041.464971e+08151.649937302.5368989.776948e+091.50.0
92010-01-1044906900.01.267791e+08175600000.013568000.068026000.0257194000.054051541.1014548016.0861161166.251.297607e+08198.853937347.4071639.761770e+091.50.0
fechaaportes_energiademandadisp_dec_hidraulicadisp_dec_no_termicadisp_dec_termicadisponibilidad_declaradagen_hidraulicagen_no_termicagen_termicageneracionprecio_bolsaprecio_ofertavol_utilindice_ONIvertimientos
36422019-12-22112768800.01.832929e+08225291120.07682440.0103329580.0336303140.01.190737e+085098331.3458204436.991.823765e+08338.309047309.4330651.121751e+100.50.000000e+00
36432019-12-23102009100.02.007886e+08230231920.07673440.0103749450.0341654810.01.304163e+085123524.4963413860.761.989537e+08351.480130305.6429031.119585e+100.50.000000e+00
36442019-12-2493062800.01.882834e+08233303480.07637440.0102359650.0343300570.01.179705e+085032989.4263613392.701.866169e+08312.589853307.0014521.116623e+100.50.000000e+00
36452019-12-25114902800.01.670771e+08232441360.07542440.0104011580.0343995380.01.058000e+084698737.2853389898.451.638887e+08275.691717303.4713391.118458e+100.50.000000e+00
36462019-12-26138478200.01.965990e+08227345760.07637440.0104832850.0339816050.01.207768e+084365842.6466974166.701.921168e+08328.319732308.1353391.119751e+100.50.000000e+00
36472019-12-27100303900.01.982598e+08232693800.07599440.0104551350.0344844590.01.250668e+084106171.0664368474.661.935414e+08331.918402307.4359031.117787e+100.50.000000e+00
36482019-12-2880942900.01.921742e+08232534280.07493440.0104865280.0344893000.01.304055e+084890928.0952769349.451.880658e+08279.387930311.2019681.112934e+100.50.000000e+00
36492019-12-2978816500.01.796031e+08235466080.07492440.0104908580.0347867100.01.203988e+084056935.5650588485.891.750443e+08246.472593326.9294841.108964e+100.50.000000e+00
36502019-12-30110690400.01.902380e+08229495920.08948440.0104772850.0343217210.01.290546e+085109396.8852338556.021.865025e+08323.892900314.1403551.107393e+100.50.000000e+00
36512019-12-31167617400.01.747399e+08235115320.08884440.0104702350.0348702110.01.138374e+084528824.7551810625.291.701769e+08274.955105324.8441291.112610e+100.58.970006e+06